Control Channel Isolation in SDN Virtualization: A Machine Learning Approach

Yeonho Yoo, Gyeongsik Yang, Changyong Shin, Jeunghwan Lee, Chuck Yoo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Performance isolation is an essential property that network virtualization must provide for clouds. This study addresses the performance isolation of the control plane in virtualized software-defined networking (SDN), which we call control channel isolation. First, we report that the control channel isolation is seriously broken in the existing network hypervisor in that the end-to-end control latency grows by up to 15 x as the number of virtual switches increases. This jeopardizes the key network operations, such as routing, in datacenters. To address this issue, we take a machine learning approach that learns from the past control traffic as time-series data. We propose a new network hypervisor, Meteor, that designs an LSTM autoencoder to predict the control traffic per virtual switch. Our evaluation results show that Meteor improves the processing latency per control message by up to 12.7x. Furthermore, Meteor reduces the end-to-end control latency by up to 73.7%, which makes it comparable to the non-virtualized SDN.

Original languageEnglish
Title of host publicationProceedings - 23rd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGrid 2023
EditorsYogesh Simmhan, Ilkay Altintas, Ana-Lucia Varbanescu, Pavan Balaji, Abhinandan S. Prasad, Lorenzo Carnevale
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages273-285
Number of pages13
ISBN (Electronic)9798350301199
DOIs
Publication statusPublished - 2023
Event23rd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGrid 2023 - Bangalore, India
Duration: 2023 May 12023 May 4

Publication series

NameProceedings - 23rd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGrid 2023

Conference

Conference23rd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGrid 2023
Country/TerritoryIndia
CityBangalore
Period23/5/123/5/4

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • Control channel
  • Isolation
  • LSTM autoencoder
  • Machine learning
  • Network virtualization
  • SDN

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Control and Optimization
  • Hardware and Architecture
  • Information Systems

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